Male courtship behaviour - aDN > TNT

Setup

library("tidyverse")
library("ggpubr")
library("zoo")
setwd("/mnt/LocalData/behaviour/aDN/aDN_behaviour")

Colours …

gg_color_hue <- function(n) {
  hues = seq(15, 375, length = n + 1)
  hcl(h = hues, l = 65, c = 100)[1:n]
}

gg_color_hue(2)

[1] "#F8766D" "#00BFC4"

genotypes <- read_tsv("../2019_03_06_Courtship/genotype.tsv",col_names = TRUE)
genotypes

# indices_list <- list.files("raw data/") %>% str_subset("_Indices.csv")
indices_list <- list.files("../2019_03_06_Courtship/",recursive = TRUE) %>% str_subset("_Indices.csv") %>% str_subset("Male")
all_indices <- tibble()
for (indices_file in indices_list) {
  video_name <- indices_file %>% str_remove("/.*")
  temp <- read_csv(paste0("../2019_03_06_Courtship/",indices_file))
  temp <- temp %>%
    mutate(video = video_name)
  all_indices <- bind_rows(all_indices,temp)
}
all_indices

all_male_indices <- left_join(x = genotypes,y = all_indices,by=c("video"="video","fly_id"="FlyId"))

ggplot(all_male_indices,aes(x=genotype,y=CourtshipIndexWithFacing)) + 
  geom_boxplot()

p1 <- ggplot(all_male_indices,aes(x=genotype,y=CourtshipIndex)) + 
  geom_boxplot()
p2 <- ggplot(all_male_indices,aes(x=genotype,y=CourtshipIndexWithFacing)) + 
  geom_boxplot()
p3 <- ggplot(all_male_indices,aes(x=genotype,y=TotalCCI)) + 
  geom_boxplot()
p4 <- ggplot(all_male_indices,aes(x=genotype,y=TotalCCIwFacing)) + 
  geom_boxplot()
ggarrange(plotlist = list(p1,p2,p3,p4),
          # labels = c("ApproachingIndex",
          #            "ContactIndex",
          #            "EncirclingIndex",
          #            "FacingIndex",
          #            "TurningIndex",
          #            "WingIndex"),
          # hjust = 1,
          ncol = 4,
          nrow = 1)

p1 <- ggplot(all_male_indices,aes(x=genotype,y=ApproachingIndex)) + 
  geom_boxplot()
p2 <- ggplot(all_male_indices,aes(x=genotype,y=ContactIndex)) + 
  geom_boxplot()
p3 <- ggplot(all_male_indices,aes(x=genotype,y=EncirclingIndex)) + 
  geom_boxplot()
p4 <- ggplot(all_male_indices,aes(x=genotype,y=FacingIndex)) + 
  geom_boxplot()
p5 <- ggplot(all_male_indices,aes(x=genotype,y=TurningIndex)) + 
  geom_boxplot()
p6 <- ggplot(all_male_indices,aes(x=genotype,y=WingIndex)) + 
  geom_boxplot()
ggarrange(plotlist = list(p1,p2,p3,p4,p5,p6),
          # labels = c("ApproachingIndex",
          #            "ContactIndex",
          #            "EncirclingIndex",
          #            "FacingIndex",
          #            "TurningIndex",
          #            "WingIndex"),
          # hjust = 1,
          ncol = 3,
          nrow = 2)

p1 <- ggplot(all_male_indices,aes(x=genotype,y=CourtshipInitiation)) + 
  geom_boxplot()
p2 <- ggplot(all_male_indices,aes(x=genotype,y=CourtshipTermination)) + 
  geom_boxplot()
p3 <- ggplot(all_male_indices,aes(x=genotype,y=CourtshipDuration)) + 
  geom_boxplot()
ggarrange(plotlist = list(p1,p2,p3),
          ncol = 3,
          nrow = 1)

df <- all_male_indices %>%
  select(genotype,CourtshipTermination) %>% 
  group_by(genotype) %>% 
  mutate(len=length(CourtshipTermination))
#ggplot(df,aes(x=CourtshipTermination,color=genotype)) + geom_step(aes(len=len,y=..y.. * len),stat="ecdf") 
ggplot(df,aes(x=CourtshipTermination,color=genotype)) + geom_step(aes(y=..y..),stat="ecdf")

df <- all_male_indices %>%
  select(genotype,CourtshipDuration) %>% 
  group_by(genotype) %>% 
  mutate(len=length(CourtshipDuration))
#ggplot(df,aes(x=CourtshipDuration,color=genotype)) + geom_step(aes(len=len,y=..y.. * len),stat="ecdf") 
ggplot(df,aes(x=CourtshipDuration,color=genotype)) + geom_step(aes(y=..y..),stat="ecdf")

p1 <- ggplot(all_male_indices,aes(x=genotype,y=ApproachingBoutLength)) + 
  geom_boxplot()
p2 <- ggplot(all_male_indices,aes(x=genotype,y=ContactBoutLength)) + 
  geom_boxplot()
p3 <- ggplot(all_male_indices,aes(x=genotype,y=EncirclingBoutLength)) + 
  geom_boxplot()
p4 <- ggplot(all_male_indices,aes(x=genotype,y=FacingBoutLength)) + 
  geom_boxplot()
p5 <- ggplot(all_male_indices,aes(x=genotype,y=TurningBoutLength)) + 
  geom_boxplot()
p6 <- ggplot(all_male_indices,aes(x=genotype,y=WingBoutLength)) + 
  geom_boxplot()
p7 <- ggplot(all_male_indices,aes(x=genotype,y=ApproachingBoutInterval)) + 
  geom_boxplot()
p8 <- ggplot(all_male_indices,aes(x=genotype,y=ContactBoutInterval)) + 
  geom_boxplot()
p9 <- ggplot(all_male_indices,aes(x=genotype,y=EncirclingBoutInterval)) + 
  geom_boxplot()
p10 <- ggplot(all_male_indices,aes(x=genotype,y=FacingBoutInterval)) + 
  geom_boxplot()
p11 <- ggplot(all_male_indices,aes(x=genotype,y=TurningBoutInterval)) + 
  geom_boxplot()
p12 <- ggplot(all_male_indices,aes(x=genotype,y=WingBoutInterval)) + 
  geom_boxplot()
ggarrange(plotlist = list(p1,p2,p3,p4,p5,p6,
                          p7,p8,p9,p10,p11,p12),
          # labels = c("ApproachingIndex",
          #            "ContactIndex",
          #            "EncirclingIndex",
          #            "FacingIndex",
          #            "TurningIndex",
          #            "WingIndex"),
          # hjust = 1,
          ncol = 6,
          nrow = 2)

#all_rawdata <- full_join(x = all_rawdata, y = genotypes, by = c("FileName"="video","Id"="fly_id"))
all_rawdata <- all_rawdata %>%
  full_join(x = all_rawdata, y = genotypes, by = c("FileName"="video","Id"="fly_id")) %>% 
  replace_na(list(genotype = "CS female"))
# sum(is.na(all_rawdata$genotype))
# summary(all_rawdata$genotype)
# unique(all_rawdata$genotype)
all_rawdata

# # Extract density data to average
# p <- ggplot_build(test_plot)
# ggplot(as.data.frame(p$data[[1]]), aes(x,y)) + geom_line()
# ggplot(as.data.frame(p$data[[2]]), aes(x,y)) + geom_line()

D genotype distance to other

all_rawdata <- all_rawdata %>%  
  unite("unique_fly",FileName,Id, remove = FALSE) %>% 
  group_by(unique_fly) %>% 
  mutate(
    Multitasking = (Approaching + Encircling + Contact + Turning + WingGesture),
    MultitaskingWithFacing = (Approaching + Encircling + Facing + Contact + Turning + WingGesture),
    Courtship = ifelse(Multitasking>=1, 1, 0),
    CourtshipWithFacing = ifelse(MultitaskingWithFacing>=1, 1, 0),
    MultitaskingWithCopulation = (Approaching + Encircling + Contact + Turning + WingGesture + Copulation),
    MultitaskingWithCopulationWithFacing = (Approaching + Encircling + Facing + Contact + Turning + WingGesture + Copulation),
    CourtshipAndCopulation = ifelse(MultitaskingWithCopulation>=1, 1, 0),
    CourtshipAndCopulationWthFacing = ifelse(MultitaskingWithCopulationWithFacing>=1, 1, 0),
    SmoothedCourtship = ifelse((rollmean(Courtship, 150, fill = c(0,0,0), align = c("left")))>0.5, 1, 0),
    SmoothedCopulation = ifelse((rollmean(Copulation, 1250, fill = c(0,0,0), align = c("center")))>0.5, 1, 0),
    SmoothedDistToOther = ifelse((rollmean(ifelse(dist_to_other__mm > 2, 1, 0), 250, fill = c(1,1,NA), align = c("center")))>0.5, 1, 0)
)

D genotype distance to other

mean distance to other

median distance to other

mean facing angle

median facing angle

median facing angle by sector

mean facing angle by sector

mean facing angle by wee sectors

counts in wee sectors

Total time in sector

Proportion time in sector

Total time in sector

Proportion time in sector

Total count in inner ring

Proportion count in inner ring

Left vs Right wing

calculate_indices <- function(input,){
  
  
  
  
  
  
  
  
  
}